Computing the Optimally Fitted Spike Train for a Synapse
T. Natschlaeger and W. Maass
Experimental data have shown that synapses are heterogeneous: different
synapses respond with different sequences of amplitudes of postsynaptic
responses to the same spike train. Neither the role of synaptic dynamics
itself nor the role of the heterogeneity of synaptic dynamics for
computations in neural circuits is well understood. We present in this
article two computational methods that make it feasible to compute for a
given synapse with known synaptic parameters the spike train that is
optimally fitted to the synapse in a certain sense. With the help of these
methods one can compute for example the temporal pattern of a spike train
(with a given number of spikes) that produces the largest sum of postsynaptic
responses for a specific synapse. Several other applications are also
discussed. To our surprise we find that most of these optimally fitted spike
trains match common firing patterns of specific types of neurons that are
discussed in the literature. Hence our analysis provides a possible
functional explanation for the experimentally observed regularity in the
combination of specific types of synapses with specific types of neurons in
Reference: T. Natschlaeger and W. Maass.
Computing the optimally fitted spike train for a synapse.
Neural Computation, 13(11):2477-2494, 2001.